Neural engineer Polina Anikeeva, Associate Professor of Materials Science and Engineering at MIT, offers a great TEDx talk on the differences in natural ‘brain hardware' and solid-state electronics.

It's a distinction that she says leads to a possible collaboration between human and artificial intelligence.

Anikeeva opens her talk by stating that, ‘When can I upload my brain to a computer?' is an ill-posed question. What she should be asking, she says, is ‘When will my brain be able to collaborate with a computer?' Machine intelligence and human intelligence are fundamentally different; the human brain is a generalist, a machine brain is a specialist.

We love her comparison between a computer, which is a set of transistors with only 3 neighbors, and the brain – where each neuron has 6,000 connections. Such intelligence would require a few million modern laptops! Building on this premise, there are many interesting insights presented in this talk, including the following snippets:

• The biggest problem is that we do not understand how this multitude of parallel signals and computations in your human brain translates into your human intelligence. The interface between human and machine intelligence is so poor that science fiction characters use verbal input to talk to machines.
• What we need is a brain-inspired machine interface. We are orders of magnitude away from trillions of synapses.
• AI develops faster than the man-machine interface research.
• We are missing the opportunity of an AI as a specialist plugin into your generalist’s brain. So, why should we spend energy in uploading this compact generalist into an army of specialist machines?

In Anikeeva's opinion, we need a paradigm shift from machine inspired electronics to a biology-driven design of new materials and architectures. We cannot just outsource this task to a handful of academic labs: it will take too long and we will miss an opportunity to gain a collaborator and a partner in AI.

She calls to join forces (academics, industries, and governments) in the development of a neural interface such that our generalist human intelligence can collaborate with specialist artificial intelligence to do what it does best: to create, analyze, and decide.

Guest post by The Futures Agency content curator Petervan

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